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Afternoon Data Analyst R Programming Jobs in Utah

Jobtailor

Data Scientist

Lehi, UT · On-site

$90 - $130/hr

... engineers, product teams, subject-matter experts, and stakeholders on end-to-end analytical ... Exposure to R or other data science and statistical tools * Experience with Power BI, Tableau, or ...

New

Raytheon

Principal Analyst Data Manager

Provo, UT

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Raytheon brings the strength of more than 100 years of experience and renowned engineering ... We are hiring a Principal Analyst Data Manager to work onsite in Tucson, Arizona. What You Will Do

Lendingclub Corporation

Sr Compliance Data Analyst

Lehi, UT · Hybrid

  • Medical

  • Dental

  • Vision

  • Retirement

... analytics professional to join the team. In this role, you will be responsible for developing ... and Data Engineering to support deliverables * Perform ongoing User-Acceptance Testing (UAT) to ...

GE Healthcare

Service Data Scientist

Salt Lake City, UT · On-site

Develop analytics to address customer needs and opportunities. Work alongside software developers ... R, Python) Demonstrated skill at data cleansing, data quality assessment, and using analytics for ...

Gehc

Service Data Scientist

Salt Lake City, UT

Develop analytics to address customer needs and opportunities. Work alongside software developers ... R, Python) Demonstrated skill at data cleansing, data quality assessment, and using analytics for ...

GE HealthCare

Service Data Scientist

Salt Lake City, UT · On-site

... analytics to address customer needs and opportunities. • Work alongside software developers and ... SPSS, R, Python) • Demonstrated skill at data cleansing, data quality assessment, and using ...

L3HHCM20

Lead, Data Architect

Salt Lake City, UT

Experience with programming languages and tools commonly used in AI/ML workflows (e.g., Python, R ... data, analytics, cloud, or project delivery are beneficial. WORK ENVIRONMENT Collaborative and ...

PACS

Senior DataBI Analyst

Salt Lake City, UT · On-site

$83K - $105K/yr

Required : • 3-5 years of experience in a data analytics, data engineering, or BI analyst role. • Proven ability to build and manage data pipelines independently, from ingestion to reporting. • ...

RS Hughes Co., Inc.

Senior Data Engineer

Salt Lake City, UT · On-site

$103K - $140K/yr

  • Medical

  • Dental

  • Life

  • Retirement

  • PTO

Job Summary R.S. Hughes is seeking a Senior Data Engineer to support and evolve our enterprise analytics platform. This role is responsible for designing, building, and maintaining scalable data ...

KIHOMAC

Data Management Analyst

Layton, UT

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Provide support to Project Manager, Contracting, or senior-level Engineering personnel in the areas ... contracting, limited data analyses, database development or data gathering, preparation of ...

KIHOMAC

Data Management Analyst

Layton, UT · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Provide support to Project Manager, Contracting, or senior-level Engineering personnel in the areas ... contracting, limited data analyses, database development or data gathering, preparation of ...

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All JobsAfternoon Data Analyst R Programming JobsAfternoon Data Analyst R Programming Jobs in Utah

Afternoon Data Analyst R Programming information

What is an afternoon data analyst r programming?

An Afternoon Data Analyst specializing in R Programming is a data professional who primarily works afternoon shifts and uses the R programming language to analyze, interpret, and visualize data. Their responsibilities typically include cleaning data, performing statistical analyses, and generating reports to support business decisions. They may work across various industries, collaborating with teams to provide insights and automate data processes using R. Afternoon shifts can be ideal for organizations that operate globally or require data support outside standard business hours. Proficiency in R, statistical techniques, and data visualization tools are essential skills for this role.

What are the key skills and qualifications needed to thrive as an afternoon data analyst specializing in R programming?

To thrive as an Afternoon Data Analyst specializing in R Programming, you need a strong background in statistics, data analysis, and proficiency with R, often supported by a degree in a quantitative field. Experience with data visualization tools, R packages (like tidyverse), and familiarity with databases or version control systems (such as Git) is typically required. Critical thinking, attention to detail, and effective communication are essential soft skills for interpreting results and presenting insights to stakeholders. These skills ensure accurate data-driven decisions, efficient workflow, and the ability to translate complex data into actionable business strategies.

What are some common challenges faced by afternoon data analysts working with R programming, and how can they be addressed?

Afternoon Data Analysts using R Programming often encounter challenges such as handling large datasets efficiently, ensuring code reproducibility, and collaborating with team members across different shifts. To address these, it's helpful to utilize R packages designed for big data (like data.table or dplyr), maintain clear and well-documented scripts, and use version control systems like Git for seamless collaboration. Regular communication with team members during shift handovers and leveraging collaborative tools can also enhance workflow and reduce misunderstandings.

What is the difference between Afternoon Data Analyst R Programming vs Morning Data Analyst R Programming?

AspectAfternoon Data Analyst R ProgrammingMorning Data Analyst R Programming
Required CredentialsBachelor's in Data Science, Statistics, or related field; R programming skillsBachelor's in Data Science, Statistics, or related field; R programming skills
Work EnvironmentTypically in office settings, working during afternoon hoursOffice environment, working during morning hours
Employer & Industry UsageUsed in industries with shift-based operations like finance, healthcareCommon in similar industries, often with flexible scheduling
Search & Comparison IntentPeople comparing different shift roles or schedules in data analysisSimilar search intent focusing on shift timing differences

The main difference between Afternoon Data Analyst R Programming and Morning Data Analyst R Programming lies in their work hours. Both roles require similar skills, credentials, and are used in comparable industries. The choice depends on personal schedule preferences and employer shift structures.

What are the most commonly searched types of Data Analyst R Programming jobs in Utah?

The most popular types of Data Analyst R Programming jobs in Utah are:

What are popular job titles related to Afternoon Data Analyst R Programming jobs in Utah?

For Afternoon Data Analyst R Programming jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Afternoon Data Analyst R Programming jobs in Utah look for?

The top searched job categories for Afternoon Data Analyst R Programming jobs in Utah are:

What cities in Utah are hiring for Afternoon Data Analyst R Programming jobs?

Cities in Utah with the most Afternoon Data Analyst R Programming job openings:

Afternoon Data Analyst R Programming jobs near you
Infographic showing various Afternoon Data Analyst R Programming job openings in Utah as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Data Scientist

Jobtailor

Lehi, UT • On-site

$90 - $130/hr

Other

Posted 3 days ago

New

Job description

  • Analyze structured and unstructured datasets to identify trends and answer business questions
  • Develop, test, and refine statistical and analytical models
  • Contribute to analytics capabilities aligned with product roadmaps, customer needs, and business use cases
  • Partner with data warehouse engineers, data engineers, product teams, subject-matter experts, and stakeholders on end-to-end analytical solutions
  • Prepare, clean, transform, and validate data for analysis, modeling, reporting, and experimentation
  • Evaluate new data sources and analytical methods
  • Document analytical approaches and communicate findings
  • Support deployment and ongoing improvement of data science solutions
Requirements
  • 2–4 years’ experience in data science, analytics, statistical modeling, or a related field, including relevant internships, academic projects, or applied professional experience
  • Working knowledge of Python and SQL
  • Understanding of statistical methods, model evaluation, and analytical problem-solving
  • Experience identifying patterns, testing hypotheses, and communicating actionable findings from datasets
  • Familiarity with database concepts, data warehousing, or data-processing workflows
  • Strong written and verbal communication skills
  • Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field, or equivalent practical experience
  • Coursework, academic projects, certifications, or early professional experience involving artificial intelligence, machine learning, or generative AI
  • Experience with pandas, NumPy, scikit-learn, or similar analytical tools
  • Exposure to AI or machine-learning tools, frameworks, APIs, or cloud-based AI services
  • Experience applying AI or machine learning to practical business, product, or customer use cases
  • Exposure to R or other data science and statistical tools
  • Experience with Power BI, Tableau, or MicroStrategy
  • Familiarity with cloud data platforms, distributed data-processing environments, or production analytics workflows
Core Competencies

Demonstrates expertise in data analysis, statistical modeling, and machine learning, with proficiency in Python and SQL. Capable of collaborating with cross-functional teams to develop and implement data-driven solutions that address business needs.

Highest-signal resume keywords
  • Data Analysis
  • Statistical Modeling
  • Python Programming
  • SQL Proficiency
  • Machine Learning
ATS Optimization Keywords Hard Skills
  • Data Science
  • Statistical Methods
  • Model Evaluation
  • Data Cleaning
  • Data Transformation
  • Pattern Identification
  • Hypothesis Testing
  • Analytical Problem-Solving
  • Data Visualization
  • Cloud-Based AI Services
Soft Skills
  • Strong Communication Skills
Industry Keywords
  • Data Warehousing
  • Data Processing Workflows
  • Distributed Data Processing
  • Business Use Cases
  • Analytics Capabilities
Tools & Technologies
  • Pandas
  • NumPy
  • Scikit-Learn
  • Power BI
  • Tableau
  • MicroStrategy
  • AI Tools
  • Machine Learning Frameworks
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